Translation of fuzzy queries for relational database system

The concept of a database skeleton which reflects both the user's conception of the real world and the system's understanding of the interrelationships among database entities is described. It consists of a conceptual schema (conceptual graphs) and a relational schema (information graph). With the aid of the database skeleton, fuzzy queries can be translated and disambiguated by analyzing the queries using the conceptual graphs of a database skeleton. The query language XQL is introduced, and the XQL translator is described in some detail.     

Fuzzy query translation for relational database systems

The paper presents a new method for fuzzy query translation based on the alpha-cuts operations of fuzzy numbers. This proposed method allows the retrieval conditions of SQL queries to be described by fuzzy terms represented by fuzzy numbers. It emphasizes friendliness and flexibility for inexperienced users. The authors have implemented a fuzzy query translator to translate user's fuzzy queries into precise queries for relational database systems. Because the proposed method allows the user to construct his fuzzy queries intuitively and to choose different retrieval threshold values for fuzzy query translation, the existing relational database systems will be more friendly and more flexible to the users.     

CMS实验中关系数据库的精确关键词查询

在大型强子对撞机(LHC)上紧凑型缪子螺线管探测器(CMS)实验的复杂数据环境下,有多个关系型数据源记录了关于数据组织和分布的信息。为实现数据查询系统的精确关键词查询功能,通过分析数据库模式图的方法,将关键词查询语言动态翻译成SQL语言,设计并实现一个跨数据库平台的关键词查询系统。针对动态翻译过程中存在的二义性问题,提出基于查询实体的模式图分析算法,以及基于最小权重树查找的动态连接算法。实验结果表明,该动态连接算法能为关键词查询正确生成所需数据库表的连接方式,使关键词查询系统具有较高的查询效率,以满足用户实时、精确查询的需求。     

Semantics preserving SPARQL-to-SQL translation

Most existing RDF stores, which serve as metadata repositories on the Semantic Web, use an RDBMS as a backend to manage RDF data. This motivates us to study the problem of translating SPARQL queries into equivalent SQL queries, which further can be optimized and evaluated by the relational query engine and their results can be returned as SPARQL query solutions. The main contributions of our research are: (i) We formalize a relational algebra based semantics of SPARQL, which bridges the gap between SPARQL and SQL query languages, and prove that our semantics is equivalent to the mapping-based semantics of SPARQL; (ii) Based on this semantics, we propose the first provably semantics preserving SPARQL-to-SQL translation for SPARQL triple patterns, basic graph patterns, optional graph patterns, alternative graph patterns, and value constraints; (iii) Our translation algorithm is generic and can be directly applied to existing RDBMS-based RDF stores; and (iv) We outline a number of simplifications for the SPARQL-to-SQL translation to generate simpler and more efficient SQL queries and extend our defined semantics and translation to support the bag semantics of a SPARQL query solution. The experimental study showed that our proposed generic translation can serve as a good alternative to existing schema dependent translations in terms of efficient query evaluation and/or ensured query result correctness.     

基于图数据库的大规模配置管理数据库关联查询

在基于关系型数据库构建的大规模配置管理数据库（CMDB）中,根据业务场景实现的关联查询功能,存在查询分析语句构造复杂、执行时间长的性能问题。为解决该问题,提出利用图数据库来实现关联查询的方法。利用配置项间的关系与图数据结构的一致性,构建基于图数据库的配置项关系表达,设计并实现一个基于图数据库的关联查询模块,以松耦合的方式集成到现有的配置管理数据库中,达到快速关联查询的目标。实验表明,本文的方法能有效解决大规模关系型数据库CMDB关联查询的性能问题。     

Database Skeleton and Its Application to Logical Database Synthesis

This paper presents the concept of a model of database skeleton which is used to represent user's knowledge on the meaning of the data. The logical database synthesis pfoblem is then formulated as a problem of convetting a partially specified database skeleton to a completely specified-one, which corresponds to one of several data models. Approaches to optimal logical database synthesis for the relational database are then considered.     

Content-based image retrieval based on a fuzzy approach

A typical content-based image retrieval (CBIR) system would need to handle the vagueness in the user queries as well as the inherent uncertainty in image representation, similarity measure, and relevance feedback. We discuss how fuzzy set theory can be effectively used for this purpose and describe an image retrieval system called FIRST (fuzzy image retrieval system) which incorporates many of these ideas. FIRST can handle exemplar-based, graphical-sketch-based, as well as linguistic queries involving region labels, attributes, and spatial relations. FIRST uses fuzzy attributed relational graphs (FARGs) to represent images, where each node in the graph represents an image region and each edge represents a relation between two regions. The given query is converted to a FARG, and a low-complexity fuzzy graph matching algorithm is used to compare the query graph with the FARGs in the database. The use of an indexing scheme based on a leader clustering algorithm avoids an exhaustive search of the FARG database. We quantify the retrieval performance of the system in terms of several standard measures.     

基于协作表示和模糊渐进最大边界嵌入的特征抽取方法

针对图嵌入方法在构造邻域关系图的过程中,简单地将样本数据划入某一类的做法并不妥当的问题,提出了模糊渐进的隶属度表示方法。该方法借助模糊数学的思想,通过模糊渐进的隶属度,将样本归属于不同类别。针对图嵌入方法中分类器效率偏低的问题,引入了协作表示分类方法,该分类方法大幅度提高了算法的计算效率。基于这两点,提出了基于协作表示和模糊渐进最大边界嵌入的特征抽取算法。在ORL、AR人脸数据库上,以及USPS数字手写体数据库上的实验表明,该算法优于主成分分析(PCA)、线性鉴别分析(LDA)、局部保留投影(LPP)和边界Fisher分析(MFA)。     

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

Over the past era, subgraph mining from a large collection of graph database is a crucial problem. In addition, scalability is another big problem due to insufficient storage. There are several security challenges associated with subgraph mining in today’s on-demand system. To address this downside, our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs (BCCA-LSDG). The two-fold process is handled in the proposed BCCA-LSDG: graph indexing and authenticated query search (query processing). A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed architecture. To resolve the issues and provide safe big data transmission, the proposed technique also combines blockchain with a consensus algorithm architecture. Security of the big data is ensured by dividing the BC network into distinct networks, each with a restricted number of allowed entities, data kept in the cloud gate server, and data analysis in the blockchain. The consensus algorithm is crucial for maintaining the speed, performance and security of the blockchain. Then Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature sets. Finally, the graph index refinement process is undertaken to improve the query results. Concerning query error, fuzzy logic is used to refine the index of the graph dynamically. The proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems, and the combination of blockchain and subgraph provides a secure communication platform, according to the findings.     

Graph Grammars for Querying Graph-like Data

Recently research has deeply investigated the problem of querying semi-structured data and data which can be represented by means of graphs (e.g. object-oriented data, XML data, etc.). Typically queries on graph-like data, called path queries, are expressed by means of regular expressions denoting paths in the graph. The result of a path query is the set of nodes reachable by means of a path expressed by a specified regular expression. In this paper we investigate the problem of extracting a subgraph satisfying a given property from a given graph representing some information. We propose a new form of queries, called graph queries, whose answers are (marked) graphs having a particular structure, extracted from the source graph. We show that a simple form of graph grammars can be profitably used to define graph queries. The result of a graph query, using a grammar G over a database D, is a marked subgraph of D ‘matching’ a graph derived from G. We consider different types of graph grammars which can be used to query graph-like data and consider their expressiveness and complexity.     

Utilizing similarity relationships among existing data for high accuracy processing of content-based image retrieval

Retrieving similar images based on its visual content is an important yet difficult problem. We propose in this paper a new method to improve the accuracy of content-based image retrieval systems. Typically, given a query image, existing retrieval methods return a ranked list based on the similarity scores between the query and individual images in the database. Our method goes further by relying on an analysis of the underlying connections among individual images in the database to improve this list. Initially, we consider each image in the database as a query and use an existing baseline method to search for its likely similar images. Then, the database is modeled as a graph where images are nodes and connections among possibly similar images are edges. Next, we introduce an algorithm to split this graph into stronger subgraphs, based on our notion of graph’s strength, so that images in each subgraph are expected to be truly similar to each other. We create for each subgraph a structure called integrated image which contains the visual features of all images in the subgraph. At query time, we compute the similarity scores not only between the query and individual database images but also between the query and the integrated images. The final similarity score of a database image is computed based on both its individual score and the score of the integrated image that it belongs to. This leads effectively to a re-ranking of the retrieved images. We evaluate our method on a common image retrieval benchmark and demonstrate a significant improvement over the traditional bag-of-words retrieval model.     

Identification- and Elimination-Based Parallel Query Processing Techniques for Object-Oriented Databases

The newly developed object-oriented database management systems provide rich facilities for the modeling and processing of structural as well as behavioral properties of complex application objects. However, due to their inherent generality, new functionalities to be added to these systems as they continue to evolve, and high performance demand in many application domains, efficient parallel algorithms and architectures would be needed to meet the performance requirement for processing large OODBs. In our previous work, we have shown that processing OODBs can be viewed as the manipulation of patterns of object associations. In this paper, we present several parallel, multiwavefront algorithms based on two approaches, i.e., identification and elimination approaches, to verify association patterns specified in queries. Both approaches allow more processors to operate concurrently on a query than the traditional tree-structured query processing approach, thus introducing a higher degree of parallelism in query processing. We present a graph model to transform the query processing problem into a graph problem. Based on the graph model, proofs of correctness of both approaches for tree-structured queries are given, and a combined approach for solving cyclic queries is also provided. We present a new data structure to represent associations between objects, parallel algorithms based on these approaches, and some evaluation results obtained from an actual implementation of these algorithms on an nCUBE 2 parallel computer.     

基于CouchDB的SPARQL查询引擎实现

传统的SPARQL查询引擎在处理查询时以三元组模式为基本单位做查询优化处理,在三元组模式较多时存在着过多的连接操作,开销比较大。文中基于文档数据库的存储和查询特点,提出一种利用主语分类的方式来存储RDF数据的方法,将不同的RDF三元组按主语分成不同的类,并存入文档数据库的文档中。在处理SPARQL查询时将三元组模式也按照主语分类,构成以主语相关块为单位的查询图,并提出一种基于属性相关性的选择度估计方法来优化查询执行计划。文中利用文档数据库CouchDB实现了新的SPARQL查询引擎,实验证明文中的方法能够提高SPARQL基本图模式查询的效率。     

A theory of translation from relational queries to hierarchicalqueries

In a heterogeneous database system, a query for one type of database system (i.e., a source query) may have to be translated to an equivalent query (or queries) for execution in a different type of database system (i.e., a target query). Usually, for a given source query, there is more than one possible target query translation. Some of them can be executed more efficiently than others by the receiving database system. Developing a translation procedure for each type of database system is time-consuming and expensive. We abstract a generic hierarchical database system (GHDBS) which has properties common to database systems whose schema contains hierarchical structures (e.g., System 2000, IMS, and some object-oriented database systems). We develop principles of query translation with GHDBS as the receiving database system. Translation into any specific system can be accomplished by a translation into the general system with refinements to reflect the characteristics of the specific system. We develop rules that guarantee correctness of the target queries, where correctness means that the target query is equivalent to the source query. We also provide rules that can guarantee a minimum number of target queries in cases when one source query needs to be translated to multiple target queries. Since the minimum number of target queries implies the minimum number of times the underlying system is invoked, efficiency is taken into consideration     

基于最小Steiner树的关键词查询方法

在关系数据库中,关键词查询无需用户学习查询语言和数据库模式相关知识,而且有效地扩大了查询范围.采用元组图描述关系数据库中元组关系,可使关键词查询问题转化为元组图的最小Steiner树求解问题.本文提出元组图上基于相似度的边权重计算方法,使边权重能够反映元组与关键词相似度的大小.然后,鉴于最小Steiner树求解问题是NP-完全问题,提出按照贪心策略执行Dijkstra算法的最小Steiner树较优解求解算法.最后,通过实验对算法进行了分析和验证.     

基于错检期望值的密文索引技术

如何提高密文数据库的查询效率是数据库加密技术面临的一个主要问题.密文索引技术是提高数据库中密文查询效率的手段之一,但现有的密文索引方法存在查询命中率低和信息泄露衡量问题.本文首先根据查询概率的实际分布情况,提出整体错检期望值的概念,以此为基础提出一种适用于非等概率查询的复合桶划分密文索引技术,并给出了相应的密文查询策略.然后,针对密文索引的信息泄露问题给出衡量和消减方法.最后,通过实验对算法进行了分析和验证.     

Intranet信息查询系统的电子邮件自动发送系统的设计和实现

在企业Ｉｎｔｒａｎｅｔ上原有的信息查询系统中增加一个电子邮件自动发送系统,该系统可以定时地给企业员工在Ｉｎｔｒａｎｅｔ上的电子信箱发送查询系统数据库中的最新信息的摘要内容,并提供一个超链接使员工可以很方便地连结到查询系统。在分析了用于电子邮件传输的ＳＭＴＰ协议的基础上,给出了该系统的Ｄｅｌｐｈｉ实现过程。     

Making Database Schema Hierarchical for Visual Access to Databases

Making the database schema hierarchical can help a casual user retrieve information from a complex database. The hierarchical database schema provides further insight into database content and focuses on meaningful data by a top-down method. The user can proceed with a hierarchical visual query, which ultimately simplifies the query, reduces the syntax error rate and conserves the query time. In this paper, we present a hierarchical graph which makes the database schema hierarchical, naturally integrates the browsing and querying and, consequently, allows the user to proceed with an incremental query on the hierarchical database schema. Also proven herein are the existence, uniformity, and consistency of the hierarchical graph to verify that the graph can be used to query the database. This paper also discusses the semantics of high-level nodes and conducts an experiment to evaluate users’ performance. Finally, we describe how one can use the hierarchical graph to unify the tasks of making the schema hierarchical, creating concept hierarchies, and integrating the databases.     

Incomplete deductive databases

We investigate the complexity of query processing in databases which have both incompletely specified data and deductive rules. The paper is divided into two parts: in the first we consider databases in which incompletely specified data occurs only in the database intension; in the second we consider databases in which incomplete information is represented only in database extension. We prove that, in general, the query processing problem for databases with incomplete intensions is undecidable. A number of classes of rules for which all conjunctive queries can be processed in polynomial time is then characterized. For databases with incomplete extensions we prove a number of CoNP completeness results. For instance, we demonstrate that processing disjunctions which are restricted to individual columns of database predicates can, in general, be as bad as processing arbitrary disjunctions (i.e. CoNP-complete). This falsifies the conjecture that such limited disjunctions could be computationally beneficial. We also show two simple examples of situations in which query processing is guaranteed to be polynomial. These situations are linked to certain assumptions about database updates.Finally, we provide a summary of the data complexity of queries depending on the type of database extension, intension, query sublanguage and Open World vs Closed World assumption.Research supported by NSF grant DCR 85-04140.More precisely, we can say this only in the presence of the closed world assumption [18].